PROJECT SUMMARY/ABSTRACT Despite the health benefits of physical activity (PA), less than 10% of older adults meet national PA guidelines. Barriers to PA range from low self-efficacy and feeling ?too old,? to limited social support. Health-related smartphone applications (apps), which are now being used to improve health behaviors, provide a promising approach to increase elder PA. However, few apps are scientifically evaluated or tailored for older adults. Our team will develop, test, and optimize a core app and specialty features?the Movn suite?which are designed to facilitate elders' PA. This suite is distinct from generic fitness apps because it blends empirical behavior change techniques in the core app (e.g., self-regulation by activity tracking), with 3 specialty features supported by social cognitive theory (SCT) and stereotype embodiment theory (SET). Specialty features include: 1) implicit and explicit messaging that promotes positive views of aging, 2) sedentary activity monitoring with peer-generated suggestions, and 3) remote coaching. To date, no other app has offered a PA- promoting suite that has been optimized to address elder inactivity. Study Aim 1 will be to assess the usability, feasibility, and acceptability of the Movn suite. Three groups of 5 older adults (age 65?90 years) will be formed. The core app and one of the three specialty features will be introduced to each group and tested by them for 2 weeks. Usability, feasibility, and acceptability will be determined by (a) analyzing usage patterns (b) examining participants' evaluations of Movn and the specialty features; and (c) identifying facilitators and barriers to app usage. We will review the data and integrate changes, upgrading the app for Aim 2. The purpose of Aim 2 will be to conduct a pilot test to examine key performance characteristics of the Movn core app and its three specialty features, through application of the Multiphase Optimization Strategy (MOST). Using a factorial design?as warranted when adopting MOST?we will randomly assign 100 underactive (i.e., accumulate <150 minutes of moderate intensity activity/week) elders to one of eight conditions which reflect all possible combinations of presence vs. absence of the three respective specialty features in conjunction with the core app. At the end of a four-month intervention period, for the core app and each specialty feature we will examine changes from baseline in objective and self-reported PA, sedentary time, and functional mobility. We will also test the association between app features and theoretically postulated mediating constructs from SCT and SET. In addition, we will document usage rates, sustained usage, and perceived usefulness in achieving PA goals for each Movn suite component. For Aim 3, we will synthesize the array of resulting data to derive specifications for an optimized Movn suite. Insofar as the currently proposed study will facilitate development of an optimized app that can be made compatible with other existing products (e.g., Fitbit), findings will be translatable to other efforts in mHealth technology. This project will also help establish a methodological foundation for future attempts to enhance PA apps via the addition of theoretically based component features.